Integration of weaviate and langchain, how to use hybrid in v4 like as_retriever in v3

cyf121232145 · March 18, 2025, 8:43pm

Description

I noticed that there is a method called as_retriever in the v3 version, which is integrated into langgraph as a tool, but I can’t find anything similar in v4. The WeaviateVectorStore library that can be integrated as a retriever only supports vector retrieval.

Server Setup Information

Weaviate Server Version:
Name: weaviate-client
Version: 4.11.1

Name: langchain-weaviate
Version: 0.0.4

DudaNogueira · March 19, 2025, 3:00pm

Hi @cyf121232145 !!

Welcome to our community

In the new integration, the similarity search already uses hybrid:

github.com/langchain-ai/langchain-weaviate

libs/weaviate/langchain_weaviate/vectorstores.py

56c874566


      
                  # raise an error because weaviate will do a fetch object query
                  # if both query and vector are None
                  raise ValueError("Either query or vector must be provided.")
              else:
                  vector = self._embedding.embed_query(query)
          
          return_uuids = kwargs.pop("return_uuids", False)
          
          with self._tenant_context(tenant) as collection:
              try:
                  result = collection.query.hybrid(
                      query=query, vector=vector, limit=k, **kwargs
                  )
              except weaviate.exceptions.WeaviateQueryException as e:
                  raise ValueError(f"Error during query: {e}")
          
          docs_and_scores: List[Tuple[Document, float]] = []
          for obj in result.objects:
              text = obj.properties.pop(self._text_key)
              filtered_metadata = {
                  k: v

Not that, because it passes all kwargs to collection.query.hybrid, you can use any of the parameters as documented here:

Is this what you are referring to? Sorry, I don’t have much experience with langgraph.

Let me know if this helps!

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Integration of weaviate and langchain, how to use hybrid in v4 like as_retriever in v3

Description

Server Setup Information

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